{"id":13476660,"url":"https://github.com/infocusp/llm_seminar_series","last_synced_at":"2025-03-27T03:30:40.280Z","repository":{"id":210909887,"uuid":"711789813","full_name":"infocusp/llm_seminar_series","owner":"infocusp","description":"Material for the series of seminars on Large Language Models","archived":false,"fork":false,"pushed_at":"2024-04-21T14:53:42.000Z","size":6170,"stargazers_count":24,"open_issues_count":1,"forks_count":8,"subscribers_count":4,"default_branch":"main","last_synced_at":"2024-12-10T10:39:23.293Z","etag":null,"topics":["course","large-language-models","llm","machine-learning","roadmap","seminar"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/infocusp.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-10-30T07:23:18.000Z","updated_at":"2024-08-22T15:28:55.000Z","dependencies_parsed_at":"2024-03-19T11:27:24.093Z","dependency_job_id":"897e9a4e-4fb6-48cd-bce2-e2bc3eea66a5","html_url":"https://github.com/infocusp/llm_seminar_series","commit_stats":null,"previous_names":["infocusp/llm_seminar_series"],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/infocusp%2Fllm_seminar_series","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/infocusp%2Fllm_seminar_series/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/infocusp%2Fllm_seminar_series/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/infocusp%2Fllm_seminar_series/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/infocusp","download_url":"https://codeload.github.com/infocusp/llm_seminar_series/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245778315,"owners_count":20670682,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["course","large-language-models","llm","machine-learning","roadmap","seminar"],"created_at":"2024-07-31T16:01:33.103Z","updated_at":"2025-03-27T03:30:39.661Z","avatar_url":"https://github.com/infocusp.png","language":"Jupyter Notebook","funding_links":[],"categories":["Jupyter Notebook"],"sub_categories":[],"readme":"# Large Language Models Seminar Series\n\n\u003cp align=\"center\"\u003eA multi-part seminar series on Large Language Models (LLMs).\u003cbr\u003e\n\u003ca href=\"https://infocusp.github.io/llm_seminar_series\"\u003e🌐 Website\u003c/a\u003e \n| \u003ca href=\"https://xmind.works/share/cmFNh1uK?xid=SjTLV1U0\"\u003e🧠 LLM Full Mind Map\u003c/a\u003e\n\u003cbr\u003e\u003cbr\u003e\n\u003ca href=\"https://zenodo.org/doi/10.5281/zenodo.10276557\"\u003e\u003cimg src=\"https://zenodo.org/badge/711789813.svg\"\u003e\u003c/img\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n![Session 1](images/home_page/Large%20Language%20Models.png)\n\n\n## ✨ [Emergence, Fundamentals and Landscape of LLMs](session_1/README.md)\n\nCovers important building blocks of what we call an LLM today, where they came from, etc. and then we'll dive into the deep universe that has sprung to life around these LLMs.\n\n![Session 1](images/home_page/Session%201.png)\n\n\n\n## ✨ Universe of Pretrained LLMs and Prompt Engineering\n\nIn this session, we will introduce various pretrained LLMs, encompassing both open source and proprietary options. We will explore different prompt engineering techniques to use pretrained LLMs for different tasks.\n\n![Session 2](images/home_page/Session%202.png)\n\n\nComing soon...\n\n## ✨ Applications of LLMs and Application Development Frameworks\n\nExplore diverse applications of Large Language Models (LLMs) and the frameworks essential for streamlined application development. Uncover how LLMs can revolutionize tasks and leverage frameworks for efficient integration into real-world applications.\n\n![Session 3](images/home_page/Session%203.png)\n\nComing soon...\n\n## ✨ [Training and Evaluating LLMs On Custom Datasets](session_1/README.md)\n\nDelve into the intricacies of training and evaluating Large Language Models (LLMs) on your custom datasets. Gain insights into optimizing performance, fine-tuning, and assessing model effectiveness tailored to your specific data.\n\n![Session 4](images/home_page/Session%204.png)\n\n## ✨ Optimizing LLMs For Inference and Deployment Techniques\n\nLearn techniques to optimize Large Language Models (LLMs) for efficient inference. Explore strategies for seamless deployment, ensuring optimal performance in real-world applications.\n\n![Session 5](images/home_page/Session%205.png)\n\nComing soon...\n\n## ✨ Open Challenges With LLMs\n\nDelve into the dichotomy of small vs large LLMs, navigating production challenges, addressing research hurdles, and understanding the perils associated with the utilization of pretrained LLMs. Explore the evolving landscape of challenges within the realm of Large Language Models.\n\n![Session 6](images/home_page/Session%206.png)\n\nComing soon...\n\n## ✨ LLM Courses\n\nList of courses to learn LLMs at your own pace.\n\nComing soon...\n\n## 💁 Contributing\n\nWe are on a generous mission to tackle the daunting FOMO in the LLM race. We need your support for technical articles and related video sessions. See [our mission](contribute/OUR_MISSION.md) for more details.\n\nFor detailed information on how to contribute, see [contribution guide](contribute/CONTRIBUTION.md).\n\n## 🌟 Contributors\n\n[![llm-seminar-series-contributors](https://contrib.rocks/image?repo=infocusp/llm_seminar_series\u0026max=2000)](https://github.com/infocusp/llm_seminar_series/graphs/contributors)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finfocusp%2Fllm_seminar_series","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finfocusp%2Fllm_seminar_series","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finfocusp%2Fllm_seminar_series/lists"}